The prevalence of underprescription or overprescription of energy needs in critically ill mechanically ventilated adults as determined by indirect calorimetry

A systematic literature review

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements.
Methods: Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10% when compared to indirect calorimetry measurements were noted at both an individual and group level.
Results: In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38% underestimated and 12% overestimated energy expenditure by more than 10%. The remaining 50% of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13–90% and 0–88% of patients, respectively. Differences of up to 43% below and 66% above indirect calorimetry values were observed.
Conclusions: Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.
Original languageEnglish
Pages (from-to)212-225
Number of pages14
JournalJournal of Parenteral and Enteral Nutrition
Volume40
Issue number2
DOIs
Publication statusPublished - Feb 2016

Keywords

  • indirect calorimetry
  • critically ill
  • nutrition
  • predictive equations
  • resting energy expenditure
  • intensive care unit

Cite this

@article{589a8aeb4af04acfad0352fe332e1d47,
title = "The prevalence of underprescription or overprescription of energy needs in critically ill mechanically ventilated adults as determined by indirect calorimetry: A systematic literature review",
abstract = "Background: Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements. Methods: Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10{\%} when compared to indirect calorimetry measurements were noted at both an individual and group level. Results: In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38{\%} underestimated and 12{\%} overestimated energy expenditure by more than 10{\%}. The remaining 50{\%} of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13–90{\%} and 0–88{\%} of patients, respectively. Differences of up to 43{\%} below and 66{\%} above indirect calorimetry values were observed. Conclusions: Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.",
keywords = "indirect calorimetry, critically ill, nutrition, predictive equations, resting energy expenditure, intensive care unit",
author = "Tatucu-Babet, {Oana A.} and Ridley, {Emma J.} and Tierney, {Audrey C.}",
year = "2016",
month = "2",
doi = "10.1177/0148607114567898",
language = "English",
volume = "40",
pages = "212--225",
journal = "Journal of Parenteral and Enteral Nutrition",
issn = "0148-6071",
publisher = "SAGE Publications Ltd",
number = "2",

}

TY - JOUR

T1 - The prevalence of underprescription or overprescription of energy needs in critically ill mechanically ventilated adults as determined by indirect calorimetry

T2 - A systematic literature review

AU - Tatucu-Babet, Oana A.

AU - Ridley, Emma J.

AU - Tierney, Audrey C.

PY - 2016/2

Y1 - 2016/2

N2 - Background: Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements. Methods: Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10% when compared to indirect calorimetry measurements were noted at both an individual and group level. Results: In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38% underestimated and 12% overestimated energy expenditure by more than 10%. The remaining 50% of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13–90% and 0–88% of patients, respectively. Differences of up to 43% below and 66% above indirect calorimetry values were observed. Conclusions: Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.

AB - Background: Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements. Methods: Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10% when compared to indirect calorimetry measurements were noted at both an individual and group level. Results: In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38% underestimated and 12% overestimated energy expenditure by more than 10%. The remaining 50% of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13–90% and 0–88% of patients, respectively. Differences of up to 43% below and 66% above indirect calorimetry values were observed. Conclusions: Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.

KW - indirect calorimetry

KW - critically ill

KW - nutrition

KW - predictive equations

KW - resting energy expenditure

KW - intensive care unit

U2 - 10.1177/0148607114567898

DO - 10.1177/0148607114567898

M3 - Article

VL - 40

SP - 212

EP - 225

JO - Journal of Parenteral and Enteral Nutrition

JF - Journal of Parenteral and Enteral Nutrition

SN - 0148-6071

IS - 2

ER -